Online analytical processing ≈ Online analytical processing
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Data Blocks Open
This work aims at reducing the main-memory footprint in high performance hybrid OLTP & OLAP databases, while retaining high query performance and transactional throughput. For this purpose, an innovative compressed columnar
\nstorage forma…
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Approximate Query Processing: What is New and Where to Go? Open
Online analytical processing (OLAP) is a core functionality in database systems. The performance of OLAP is crucial to make online decisions in many applications. However, it is rather costly to support OLAP on large datasets, especially b…
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The impact of knowledge management process and business intelligence on organizational performance Open
The aim of this study was to study the relationship between knowledge management in its operations; including knowledge generation, knowledge sharing, knowledge usage and business intelligence; including OLAP, data mining on the performanc…
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G-OLA Open
Nearly 15 years ago, Hellerstein, Haas and Wang proposed online aggregation (OLA), a technique that allows users to (1) observe the progress of a query by showing iteratively refined approximate answers, and (2) stop the query execution on…
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Challenges and Solutions for Processing Real-Time Big Data Stream: A Systematic Literature Review Open
Contribution: Recently, real-time data warehousing (DWH) and big data streaming have become ubiquitous due to the fact that a number of business organizations are gearing up to gain competitive advantage. The capability of organizing big d…
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A model-driven approach to automate data visualization in big data analytics Open
In big data analytics, advanced analytic techniques operate on big datasets aimed at complementing the role of traditional OLAP for decision making. To enable companies to take benefit of these techniques despite the lack of in-house techn…
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A view-based model of data-cube to support big earth data systems interoperability Open
Big Earth Data-Cube infrastructures are becoming more and more popular to provide Analysis Ready Data, especially for managing satellite time series. These infrastructures build on the concept of multidimensional data model (data hypercube…
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Machine Learning and OLAP on Big COVID-19 Data Open
In the current technological era, huge amounts of big data are generated and collected from a wide variety of rich data sources. These big data can be of different levels of veracity in the sense that some of them are precise while some ot…
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Implementing Multidimensional Data Warehouses into NoSQL Open
Not only SQL (NoSQL) databases are becoming increasingly popular and have some interesting strengths
such as scalability and flexibility. In this paper, we investigate on the use of NoSQL systems for
implementing OLAP (On-Line Analyt…
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Hierarchical Topic Modeling of Twitter Data for Online Analytical Processing Open
Social platforms, such as Twitter, reveal much about the tastes of the public. Many studies focus on the content analysis of social platforms, which assists in product promotion and sentiment investigation. On the other hand, online analyt…
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Array databases: concepts, standards, implementations Open
Multi-dimensional arrays (also known as raster data or gridded data) play a key role in many, if not all science and engineering domains where they typically represent spatio-temporal sensor, image, simulation output, or statistics “datacu…
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A Visual Analytics Framework for Reviewing Multivariate Time-Series Data with Dimensionality Reduction Open
Data-driven problem solving in many real-world applications involves analysis of time-dependent multivariate data, for which dimensionality reduction (DR) methods are often used to uncover the intrinsic structure and features of the data. …
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Towards scalable real-time analytics Open
We present an overview of our work on the SAP HANA Scale-out Extension, a novel distributed database architecture designed to support large scale analytics over real-time data. This platform permits high performance OLAP with massive scale…
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A Survey on Big Data for Trajectory Analytics Open
Trajectory data allow the study of the behavior of moving objects, from humans to animals. Wireless communication, mobile devices, and technologies such as Global Positioning System (GPS) have contributed to the growth of the trajectory re…
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A Layered Aggregate Engine for Analytics Workloads Open
This paper introduces LMFAO (Layered Multiple Functional Aggregate Optimization), an in-memory optimization and execution engine for batches of aggregates over the input database. The primary motivation for this work stems from the observa…
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Enabling CXL Memory Expansion for In-Memory Database Management Systems Open
Limited memory volume is always a performance bottleneck in an in-memory database management system (IMDBMS) as the data size keeps increasing. To overcome the physical memory limitation, heterogeneous and disaggregated computing platforms…
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OLAP-Tools for the Formation of Connected and Diversified Production and Project Management Systems Open
This article is devoted to the problem of the ability to represent business processes of complex systems of project and production management as a set of interacting semantically defined objects.To solve this problem, multidimensional mode…
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A Hybrid Infrastructure of Enterprise Architecture and Business Intelligence & Analytics for Knowledge Management in Education Open
Advances in science and technology, the Internet of Things, and the proliferation of mobile apps are critical factors to the current increase in the amount, structure, and size of information that organizations have to store, process, and …
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Bias in OLAP Queries Open
On line analytical processing (OLAP) is an essential element of decision-support systems. OLAP tools provide insights and understanding needed for improved decision making. However, the answers to OLAP queries can be biased and lead to per…
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Building an active semantic data warehouse for precision dairy farming Open
Digitalization of agricultural technology has led to the emergence of precision dairy farming, which strives for the simultaneous improvement of productivity as well as animal well-being in dairy farming through advanced use of technology …
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Micro-architectural Analysis of In-memory OLTP Open
Micro-architectural behavior of traditional disk-based online transaction processing (OLTP) systems has been investigated extensively over the past couple of decades. Results show that traditional OLTP mostly under-utilize the available mi…
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Maximizing Persistent Memory Bandwidth Utilization for OLAP Workloads Open
Modern database systems for online analytical processing (OLAP) typically rely on in-memory processing. Keeping all active data in DRAM severely limits the data capacity and makes larger deployments much more expensive than disk-based alte…
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End-to-end Optimization of Machine Learning Prediction Queries Open
Prediction queries are widely used across industries to perform advanced\nanalytics and draw insights from data. They include a data processing part\n(e.g., for joining, filtering, cleaning, featurizing the datasets) and a\nmachine learnin…
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The impact of business intelligence tools on sustaining financial report quality in Jordanian commercial banks Open
The objective of this study was to showcase the influence of Business Intelligence (BI) tools, such as Online Analytical Processing (OLAP), Extract, Transform, Load (ETL) processes, Data Mining (DM), Relational Database Management Systems …
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Data Cleaning In Data Warehouse: A Survey of Data Pre-processing Techniques and Tools Open
A Data Warehouse is a computer system designed for storing and analyzing an organization's historical data from day-to-day operations in Online Transaction Processing System (OLTP).Usually, an organization summarizes and copies information…
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In-Depth Analysis of Energy Efficiency Related Factors in Commercial Buildings Using Data Cube and Association Rule Mining Open
Significant amounts of energy are consumed in the commercial building sector, resulting in various adverse environmental issues. To reduce energy consumption and improve energy efficiency in commercial buildings, it is necessary to develop…
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Choosing a cloud DBMS Open
As analytic (OLAP) applications move to the cloud, DBMSs have shifted from employing a pure shared-nothing design with locally attached storage to a hybrid design that combines the use of shared-storage (e.g., AWS S3) with the use of share…
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Adaptive HTAP through Elastic Resource Scheduling Open
Modern Hybrid Transactional/Analytical Processing (HTAP) systems use an integrated data processing engine that performs analytics on fresh data, which are ingested from a transactional engine. HTAP systems typically consider data freshness…
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Database Benchmarking for Supporting Real-Time Interactive Querying of Large Data Open
In this paper, we present a new benchmark to validate the suitability of database systems for interactive visualization workloads. While there exist proposals for evaluating database systems on interactive data exploration workloads, none …
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MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems Open
Database management systems (DBMSs) are notoriously difficult to deploy and administer. The goal of a self-driving DBMS is to remove these impediments by managing itself automatically. However, a critical problem in achieving full autonomy…